Technopolis Group has an unparalleled track record in evaluation and impact assessment. Our clients, including European institutions, regional and national policymakers, international institutions and donors, have relied on us over the past 30 years for high-quality evaluation and impact assessment studies, particularly in the field of science and innovation policies.
We therefore have expertise in a broad range of evaluation activities throughout the whole policy cycle.
- Both traditional and large-scale, complex programmes
- Policies and regulations
- Both funding instruments and other types of policy interventions
- Evaluating research and innovation funding organisations as well as research performers such as universities and research institutes
- Reviewing national and regional research and innovation systems
We can link evaluation results to programme, policy and organisational redesign. We help to build and set-up wider monitoring and evaluation (M&E) frameworks, defining the most suitable indicators. We also share our experience by providing evaluation training to policymakers and practitioners.
All interventions and their specific contexts have unique characteristics. Hence, we don’t believe in pre-packaged solutions, but develop tailored approaches and cutting-edge methodologies to match the specific needs of evaluations and those who commission them. We provide evidence-based findings and recommendations to help policymakers make informed decisions on issues that matter. The methods we use include:
- Evaluation approaches
- Impact assessment design and scenario building
- Theory-based evaluation methods and contribution analysis
- Logical framework development and analysis
- Mapping of regulatory frameworks
- Sampling strategies
- Survey design and implementation
- Stakeholder consultation
- Expert panels, workshops and focus groups
- Comparative analyses and benchmarking
- Bibliometrics
- Patent analysis
- Economic analysis methods
- Econometric analyses
- Counterfactual impact evaluation methods (experimental and quasi-experimental)
- Cost-benefit analysis
- Data science methods
- Big data methods, including data and text mining
- Semantic analysis and techniques for qualitative data analysis and interpretation
- Altmetrics and social media analysis